DBMS > FoundationDB vs. HyperSQL vs. OushuDB vs. Spark SQL

System Properties Comparison FoundationDB vs. HyperSQL vs. OushuDB vs. Spark SQL

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Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

Description

Ordered key-value store. Core features are complimented by layers.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Relational DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.06
Rank	#185	Overall
	#31	Document stores
	#28	Key-value stores
	#85	Relational DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	0.10
Rank	#355	Overall
	#154	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

github.com/apple/foundationdb

hsqldb.org

www.oushu.com/product/oushuDB

spark.apache.org/sql

Technical documentation

apple.github.io/foundationdb

hsqldb.org/web/hsqlDocsFrame.html

www.oushu.com/documentation

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

FoundationDB

Oushu

Apache Software Foundation

Initial release

2013

2001

2014

Current release

6.2.28, November 2020

2.7.2, June 2023

4.0.1, August 2020

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

based on BSD license

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Scala

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux

Linux
OS X
Windows

Data scheme

schema-free

some layers support schemas

yes

Typing

predefined data types such as float or date

some layers support typing

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

supported in specific SQL layer only

yes

Full-featured ANSI SQL support

SQL-like DML and DDL statements

APIs and other access methods

HTTP API

JDBC via HTTP
JDBC
ODBC

JDBC
ODBC

Supported programming languages

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

All languages supporting JDBC/ODBC
Java

C
C++

Java
Python
R
Scala

Server-side scripts

Stored procedures

in SQL-layer only

Java, SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Linearizable consistency

Immediate Consistency

Foreign keys

Referential integrity

in SQL-layer only

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Kerberos, SSL and role based access

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